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int64
2k
2.02k
3.6.1 - Death rate due to road traffic injuries, by sex (per 100,000 population) - SH_STA_TRAF - Both sexes
float64
10.1
38.9
Algeria
DZA
2,000
22.5
Algeria
DZA
2,005
22.1
Algeria
DZA
2,010
22.3
Algeria
DZA
2,015
21.2
Algeria
DZA
2,019
20.9
Angola
AGO
2,000
25.1
Angola
AGO
2,005
26.1
Angola
AGO
2,010
25.8
Angola
AGO
2,015
23.6
Angola
AGO
2,019
26.1
Benin
BEN
2,000
28.4
Benin
BEN
2,005
28.9
Benin
BEN
2,010
28.2
Benin
BEN
2,015
27.3
Benin
BEN
2,019
26.8
Botswana
BWA
2,000
31.8
Botswana
BWA
2,005
24.8
Botswana
BWA
2,010
24.2
Botswana
BWA
2,015
24.8
Botswana
BWA
2,019
26.4
Burkina Faso
BFA
2,000
27.6
Burkina Faso
BFA
2,005
29.2
Burkina Faso
BFA
2,010
30.2
Burkina Faso
BFA
2,015
30.4
Burkina Faso
BFA
2,019
31
Burundi
BDI
2,000
30.3
Burundi
BDI
2,005
29.9
Burundi
BDI
2,010
33.2
Burundi
BDI
2,015
34.4
Burundi
BDI
2,019
35.5
Cameroon
CMR
2,000
27.4
Cameroon
CMR
2,005
28.3
Cameroon
CMR
2,010
28.9
Cameroon
CMR
2,015
29
Cameroon
CMR
2,019
30.2
Cape Verde
CPV
2,000
22.9
Cape Verde
CPV
2,005
23.8
Cape Verde
CPV
2,010
23.5
Cape Verde
CPV
2,015
25
Cape Verde
CPV
2,019
26.8
Central African Republic
CAF
2,000
32.3
Central African Republic
CAF
2,005
33.4
Central African Republic
CAF
2,010
30.5
Central African Republic
CAF
2,015
34
Central African Republic
CAF
2,019
37.7
Chad
TCD
2,000
27
Chad
TCD
2,005
24.8
Chad
TCD
2,010
24.7
Chad
TCD
2,015
25.7
Chad
TCD
2,019
32.4
Comoros
COM
2,000
26.9
Comoros
COM
2,005
26.8
Comoros
COM
2,010
27.1
Comoros
COM
2,015
26.6
Comoros
COM
2,019
26.6
Congo
COG
2,000
26.3
Congo
COG
2,005
25.5
Congo
COG
2,010
27
Congo
COG
2,015
27.6
Congo
COG
2,019
29.7
Cote d'Ivoire
CIV
2,000
25.4
Cote d'Ivoire
CIV
2,005
26.3
Cote d'Ivoire
CIV
2,010
25.8
Cote d'Ivoire
CIV
2,015
23.2
Cote d'Ivoire
CIV
2,019
24.1
Democratic Republic of Congo
COD
2,000
38.1
Democratic Republic of Congo
COD
2,005
36.8
Democratic Republic of Congo
COD
2,010
36
Democratic Republic of Congo
COD
2,015
33.5
Democratic Republic of Congo
COD
2,019
34.9
Djibouti
DJI
2,000
27.5
Djibouti
DJI
2,005
28.1
Djibouti
DJI
2,010
28.2
Djibouti
DJI
2,015
23.9
Djibouti
DJI
2,019
23.5
Egypt
EGY
2,000
11.2
Egypt
EGY
2,005
10.8
Egypt
EGY
2,010
13.7
Egypt
EGY
2,015
11.7
Egypt
EGY
2,019
10.1
Equatorial Guinea
GNQ
2,000
22.1
Equatorial Guinea
GNQ
2,005
20.1
Equatorial Guinea
GNQ
2,010
20.8
Equatorial Guinea
GNQ
2,015
23.8
Equatorial Guinea
GNQ
2,019
27.2
Eritrea
ERI
2,000
31.3
Eritrea
ERI
2,005
33.9
Eritrea
ERI
2,010
34
Eritrea
ERI
2,015
36.9
Eritrea
ERI
2,019
37.9
Eswatini
SWZ
2,000
29.9
Eswatini
SWZ
2,005
29.9
Eswatini
SWZ
2,010
30.1
Eswatini
SWZ
2,015
31.5
Eswatini
SWZ
2,019
33.5
Ethiopia
ETH
2,000
24.6
Ethiopia
ETH
2,005
24.5
Ethiopia
ETH
2,010
23.3
Ethiopia
ETH
2,015
26
Ethiopia
ETH
2,019
28.2
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Death Rate Road Traffic Injuries | Africa (Our World in Data) | Africa (Electric Sheep Africa metadata inventory)

Size category: n<1K - Formats: parquet - Sector: infrastructure_transport - Engineered by Electric Sheep Africa

size sector downloads license

TL;DR

This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.

What This Dataset Covers

Public datasets help analysts inspect structured evidence, build reproducible workflows, and compare patterns across domains.

Dataset context from the existing Hugging Face card: Death Rate Road Traffic Injuries | Africa (Our World in Data) 🌍 270 observations · 54 Africa countries · 2000–2019 · Repackaged by Electric Sheep Africa TL;DR This dataset contains 270 observations of Death Rate Road Traffic Injuries data across 54 Africa countries, spanning 2000–2019. About the source Source: Our World in Data Publisher: Our World in Data License: cc-by-4.0 Topic: Death Rate Road Traffic Injuries Geographic… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-owid-death-rate-road-traffic-injuries.

Dataset Profile

Field Value
Hugging Face repo electricsheepafrica/africa-owid-death-rate-road-traffic-injuries
Sector infrastructure_transport
Topic tags tabular, our-world-in-data, death-rate-road-traffic-injuries, owid, long-run-series, time-series
Modalities tabular, text
Formats parquet
Size category n<1K
Countries Africa-wide or source-defined African coverage
ISO3 coverage not declared
Last modified on HF 2026-06-05 01:53:47+00:00
Inventory snapshot 2026-07-16T16:00:34Z

How To Read This Dataset

  • Start from the repository files and the dataset viewer when available.
  • Treat the README context as a fast orientation layer; confirm variable definitions and units in the data files before modeling.
  • Use explicit country columns when present. When geography is only implied by the title or source metadata, document that assumption in downstream analysis.
  • Preserve missing values until you have a defensible imputation rule.

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-owid-death-rate-road-traffic-injuries")
print(ds)

split_name = next(iter(ds))
table = ds[split_name]
print(table.features)
print(table[:3])

Convert To Pandas When Tabular

from datasets import Dataset

first_split = ds[next(iter(ds))]
if isinstance(first_split, Dataset):
    df = first_split.to_pandas()
    print(df.head())

Data Quality Notes

  • This card was standardized from the Electric Sheep Africa Hugging Face metadata inventory.
  • Exact schema, row counts, and source files should be inspected in the repository data files.
  • Metadata gaps from the inventory: country, upstream_publisher.
  • Do not infer policy meaning from labels alone; confirm definitions, units, and methods in the source material.

Source And Provenance

Suggested Analyses

  • Inspect schema and missingness before modeling.
  • Profile variables by geography, time, and subgroup columns where present.
  • Join with other Electric Sheep Africa datasets using explicit country, year, and indicator fields when available.
  • Build reproducible notebooks that cite both the original source context and the Electric Sheep Africa Hugging Face repo.

Citation

@misc{electric_sheep_africa_africa_owid_death_rate_road_traffic_injuries_2026,
  title        = {Death Rate Road Traffic Injuries | Africa (Our World in Data) | Africa (Electric Sheep Africa metadata inventory)},
  author       = {Public dataset metadata},
  year         = {2026},
  url          = {https://huggingface.co/datasets/electricsheepafrica/africa-owid-death-rate-road-traffic-injuries},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-owid-death-rate-road-traffic-injuries}}
}

License

Released under CC BY 4.0.

Original source rights remain with the original publisher or data provider. Electric Sheep Africa engineering standardizes discovery metadata, documentation, and usage guidance for analysis on Hugging Face.

About Electric Sheep Africa

Electric Sheep Africa publishes ML-ready African public datasets on Hugging Face.


Provenance: metadata-backed README standardized 2026-08-12 by the Electric Sheep Africa README system. Inventory source: catalog/esa_metadata_inventory/master_metadata.jsonl.

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